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research. Experience applying machine learning and statistical modeling techniques to large biological datasets for biomarker discovery, disease prediction, or host-pathogen investigations. Proficiency in
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high-quality research in one of the Department's key research areas: (i) Artificial Intelligence and Machine Learning; (ii) Big Data and Data Management; (iii) Computer Vision and Pattern Recognition
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, including machine learning and language technologies, for the integration and analysis of clinical, advanced data harmonisation, and next generation research infrastructures. You will contribute to research
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Machine Learning; (ii) Big Data and Data Management; (iii) Computer Vision and Pattern Recognition; and (iv) Distributed Systems and Networking. These key research areas have a special thematic focus on (a
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within the project AI4TECSWriting a doctoral dissertation in computer sciencePublishing research findings in leading international conferences and high‑impact journals in AI, machine learning, and
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programming models and high-performance computing techniques and machine learning models. Practical experience in the programming of high-performance computing of AI and/or scientific computing applications
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to prepare project reports and co-author research papers. The ideal candidate is expected to be working towards a PhD in Computer Engineering, Computer Science, Computer Systems Engineering, Electronic
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. Strong (inter-)national network in field of application. Experience with high-performance computing (HPC) and large datasets. Experience with machine learning applied to geophysical signals. Experience in
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understand, explain and advance society and environment we live in. Your role The University of Luxembourg invites applications for a fully funded Ph.D. position in machine-learning force fields (MLFFs
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projects in data-driven nutrition, such as: statistical modelling, AI, and machine learning on large epidemiological cohorts, diet and health data analysis of omics data (metabolomics, proteomics, microbiome